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Reliable AAIA Test Practice, Vce AAIA Torrent

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Reliable AAIA Test Practice, Vce AAIA Torrent

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ISACA Advanced in AI Audit Sample Questions (Q174-Q179):NEW QUESTION # 174
Which of the following is the PRIMARY reason IS auditors must be aware that generative AI may return different investment recommendations from the same set of data?
  • A. Computational logic is based on probabilities.
  • B. Neural node access varies each time the process is executed.
  • C. Servers are reconfigured periodically.
  • D. Limitations can arise in the quantification of risk profiles.
Answer: A

NEW QUESTION # 175
A newly deployed fraud detection model is misclassifying transactions due to inconsistent formatting in the data stream. What is the BEST recommendation?
  • A. Define and document the technical specifications for incoming data
  • B. Train staff on fraud patterns and alert handling
  • C. Enable real-time monitoring of transaction volumes
  • D. Increase model complexity to handle more input types
Answer: A
Explanation:
Inconsistent data formatting means the AI model is receiving inputs that do not match what it was trained to understand. The best corrective action is todocument and enforce technical specificationsfor incoming data (option A).
AAIA highlights this as a fundamental data governance requirement:
* Field formats
* Data types
* Encoding rules
* Required attributes
* Normalization methods
Without strict specifications, the model cannot reliably parse or classify inputs.
Option B does not address the root cause.
Option C improves human response but not data consistency.
Increasing model complexity (D) adds risk and does not fix inconsistent formatting.
References:
AAIA Domain 2: Input Standards and Data Consistency
AAIA Domain 1: Governance and Data Pipeline Controls

NEW QUESTION # 176
Which of the following considerations should be prioritized when using an AI tool to select a sample for conducting an audit of a financial institution's transaction processing system?
  • A. The ability to process large volumes of data
  • B. The transparency of the sampling process
  • C. The speed of sample generation
  • D. The historical performance in previous audits
Answer: B
Explanation:
In an audit context,transparencyof sampling is essential for demonstrating that the sample is fair, unbiased, and aligned with the audit objectives. When an AI tool selects samples for testing financial transactions, auditors must be able to explain and defendhowthe sample was generated-particularly to management, regulators, and external stakeholders. Option A directly supports AAIA's focus onaudit planning, sampling methodologies, and AI audit evidence.
High throughput (option B) and speed (option C) are beneficial but secondary to methodological soundness and explainability. Option D (historical performance) can be helpful but does not guarantee current transparency or appropriateness in new contexts. For AI-enabled sampling, the priority is that theselection logic is understandable, documented, and reproducible, ensuring audit defensibility.
References:
ISACA,AAIA Exam Content Outline- Domain 3: AI Auditing Tools and Techniques (Audit Testing and Sampling Methodologies; Audit Evidence Collection Techniques).
ISACA auditing guidance on sampling and transparency in AI-assisted audit procedures.

NEW QUESTION # 177
Which of the following do supervised AI learning models PRIMARILY use to train algorithms?
  • A. Randomized data sets
  • B. Unlabeled data sets
  • C. Labeled data sets
  • D. Clustered data sets
Answer: C

NEW QUESTION # 178
An IS auditor is reviewing an AI application that uses customer data to refine the organization's marketing outreach strategies. Which of the following should be the auditor's PRIMARY focus during this review?
  • A. Access control design and effectiveness
  • B. Alignment with organizational AI strategies
  • C. Escalation protocols for sensitive data breaches
  • D. Compliance with applicable privacy regulations
Answer: D
Explanation:
Since the AI system processes customer data-including potentially personal, sensitive, or behavioral data- the auditor'sprimaryfocus must beprivacy compliance(C). AAIA identifies privacy violations as one of the highest-risk areas for organizations using AI.
The auditor must ensure:
* Data collection follows lawful basis requirements
* Customers gave proper consent (if required)
* Processing adheres to data minimization and purpose limitation
* Storage and retention policies meet regulatory standards
* Data subjects' rights (access, correction, deletion) are protected
* Third-party or cross-border transfers are compliant
Access controls (B) matter but are secondary to ensuring the data is legally collected and processed. AI strategy alignment (A) is governance-related, not risk-critical. Escalation protocols (D) support incident response but come after confirming lawful processing.
References:
AAIA Domain 5: Data Privacy, Lawfulness of Processing
AAIA Domain 1: Privacy and Data Governance Programs

NEW QUESTION # 179
......
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